This paper realized an electromagnetic tracking system based on electrically-controlled rotating magnetic field. A tracking system using the digital signal processor (DSP) as the control processing device was developed, including a controllable constant current source module, a magnetic field source module, a three-axis magnetic sensor and ADC interface circuit. The experimental results verified that each time the system could be stable positioning, average error of position was 0.282 cm, the average error of orientation was 0.696o, the positioning time was 1.572 s. Through calibration and further improvement of the hardware circuit, the performance of the system is expected to further improve.
Calibration ; Electromagnetic Phenomena ; Equipment Design ; Magnetic Fields

Electromagnetic tracking is a method to track the position and space attitude of objects utilizing electromagnetic field. In this paper, the main methods during the development of Electromagnetic tracking are summarized and classified according to the magnetic field generation method, the number of magnetic sources and sensors used, the configuration and geometry of them. Tracking algorithm and calibration methods are also discussed. The critical issues during the development of electromagnetic tracking are analyzed, with the hope of helping the further research and application of electromagnetic tracking.
Algorithms ; Electromagnetic Fields ; Phantoms, Imaging

Electrophysiological stimulator is widely used in study of biological electrical activities. This electrophysiological stimulator is capable of outputting both biphasic and monophasic waveforms with amplitudes within 0V and 30V. The sequence of the biphasic waveforms is alterable and their widths and interval can be respectively arbitrarily modified by the operator. The machine will inform the operator as soon as the charge completes through the indicator and buzzer. The safety of experimental objects is guaranteed by float ground thanks to battery power supply.
Electric Countershock ; instrumentation ; Electric Stimulation Therapy ; instrumentation ; Electrophysiological Phenomena ; Equipment Design

In order to control real-time sampling and achieve smooth scroll wave in the epicardial mapping system, which has 128 channels and a sampling rate of 2kHz/channel, we have designed a user interface using Direct-Draw in cooperation with multiple-thread technology and extracting method. This method has proven to be feasible in animal experiment.
Algorithms ; Animals ; Artificial Intelligence ; Body Surface Potential Mapping ; methods ; Electrophysiologic Techniques, Cardiac ; instrumentation ; methods ; Pericardium ; physiology ; Signal Processing, Computer-Assisted ; instrumentation ; Software

It is important for cardiac therapy devices such as the automated external defibrillator to discriminate different cardiac disorders based on Electrocardiogram analysis. A phase space analysis based algorithm is proposed to detect cardiac arrhythmias effectively. Firstly, the phase space of the signal is reconstructed. Then from the viewpoint of geometry and information theory, the distribution entropy of the point density in the two-dimensional reconstructed phase space is calculated as the features in the further classification. Finally the nearest-neighbour method based on Mahalanobis distance is used to classify the sinus rhythm (SR), supraventricular tachyarrhythmia (SVTA), atrial flutter (AFL) and atrial fibrillation (AF). To evaluate the sensitivity, specificity and accuracy of this proposed method in the cardiac arrhythmias classification, the MIT-BIH arrhythmias database and the canine endocardial database are studied respectively. Experiment results demonstrate that the proposed method can detect SR, SVTA, AFL and AF signals rapidly and accurately with the simple computation. It promises to find application in automated devices for cardiac arrhythmias therapy.
Algorithms ; Animals ; Arrhythmias, Cardiac ; diagnosis ; Dogs ; Electrocardiography ; methods ; Entropy ; Humans ; Signal Processing, Computer-Assisted

Atrial fibrillation (AF) is a complex and dangerous arrhythmia. The treatment method is still unefficient because of its unknown mechanism. The purpose of our research is to detect the electrical activity on the atria surface and therefore find the optimal technique to characterize AF for clinical application. All kinds of maps are presented clearly and the activity of sinus or AF rhythm can be seen quite differently. The active isopotential map can display the dynamic electrical conduction of the atrium as a movie. Sequentially the vectorgraph shows the direction of depolarization at every moment. Finally statistical results are also very useful for analysis on AF. Statistics of exciting frequency and correlation area show great difference in various channels during AF. "Source" or "sink" may be estimated by interval variance statistics. This study demonstrates the flexibility of the system in AF research. The statistical results can also be adopted to clearly express the characteristics of AF.
Animals ; Atrial Fibrillation ; diagnosis ; physiopathology ; Body Surface Potential Mapping ; methods ; Dogs ; Electrocardiography, Ambulatory ; Electrodiagnosis ; methods ; Pericardium ; physiopathology ; Swine

Objective To study the complex restitution relation between the present action potential duration (APD) and its previous diastole interval (DI) and APD. Method The Luo-Rudy model was paced with different protocols to draw the coordinate curves between the present APD and its first previous DI. These curves were fit with the artificial neural network (ANN). Result Different pacing protocols caused different coordinate curves, and there was no one-to-one relation between pre-sent APD and its first previous DI. ANN fits these curves satisfactorily. Conclusion There is a complex relation between the present APD and the APDs and Dis of the first three previous beats. This relation can be modeled accurately with ANN.

Objective To find a method for real-time measurement of epicardial electrical activity suitable for clinical application.Method Combined unipolar and bipolar mapping technique for recording epicardial electrical activity was applied to detect the propagation of depolarization wave over the epicardium.Epicardial signals from 4 pigs were sampled simultaneously during sinus rhythm or atrial fibrillation(AF).Result Active isopotential map showing the spread of excitation on epicardial surface was demonstrated and correlation analysis data were obtained.The difference in correlation coefficients between adjacent sites was evident during sinus rhythm(above 0.8) and AF(about(0.5).) Conclusion The result shows that combined unipolar and bipolar technique improves the electrode efficiency and the precision in epicardial mapping.Distribution of depolarization wave or the reentry pathway during complex arrhythmia may be revealed by correlation analysis.

Objective To explore the mechanism underlying the superiority of the biphasic waveform to monophasic waveform in defibrillation.Method The Luo-Rudy model was adjusted so that it could be used to study defibrillation.Based on the adjusted model the effects of different defibrillation waveforms on cell action potential duration(APD) were studied.Result Biphasic electrical field pulse extended the APD longer than that with monophasic one.Moreover,biphasic waveforms with different strengths could prolong the APD almost equally,while monophasic pulses with different strengths showed different ability to prolong the APD and the spatial distribution of the APD became dispersed.It was also found that the strength of electrical fields pulse contributed much to the change of APD while the duration showed little effect.Conclusion The clinical superiority of biphasic pulses to monophasic pulses in defibrillation is resulted from its ability to prolong the time course of the APD and more importantly,it causes even spatial distribution of the APD.

Objective To explore a method for real-time pretreatment and character extraction of epicardial signals and promote the research on the electrophysiological mechanism of atrial fibrillation (AF).Methods Firstly,an analysis was made to get the properties of epicardial signals. Then,a method based on template matching was used to extract atrial activities from epicardial signals. At last,the feature points of atrial activities could be recognized.Results The correctness of recognizing feature points of sinus rhythm and AF were 99.7% and 97.0% respectively. Furthermore,only 1~2 s were cost to compute a 10-second data record with this method.Conclusion The proposed method can extract crucial information about atrium depolarization from epicardial signals and is adequate for online analysis.